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when i check installation by running python3 -m alpa.test_install,AssertionError happend #960

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Ghiad opened this issue Oct 17, 2023 · 6 comments

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@Ghiad
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Ghiad commented Oct 17, 2023

Please describe the bug

Please describe the expected behavior

System information and environment

  • OS Platform and Distribution (e.g., Linux Ubuntu 16.04, docker):
  • Python version:3.95
  • CUDA version:11.3
  • NCCL version:
  • cupy version:cupy-cuda11x 12.2.0
  • GPU model and memory:A100
  • Alpa version:0.2.3
  • JAX version:0.3.22

To Reproduce
Steps to reproduce the behavior:
1.run python3 -m alpa.test_install
4. See error

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Additional information
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@Ghiad
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Ghiad commented Oct 18, 2023

it says we compiled for one device but ran on another.CUDA_VISIBLE_DEVICES=0 fixes this problem for me.However,when i run this command CUDA_VISIBLE_DEVICES=0,1,2 python3 -m alpa.test_install, another error occured , there was a AssertionError,how can i fix that?
image

@Ghiad Ghiad changed the title when i check installation by running python3 -m alpa.test_install,something error happend when i check installation by running python3 -m alpa.test_install,AssertionError happend Oct 18, 2023
@caixiiaoyang
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你有几张卡,num_stages默认是2,你的num_devices不能整除num_satges就会出现这个问题,最好保证num_devices为偶数

@Ghiad
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Ghiad commented Oct 18, 2023

你有几张卡,num_stages默认是2,你的num_devices不能整除num_satges就会出现这个问题,最好保证num_devices为偶数

我的服务器上有5张卡,如下图
image

我应该怎么修改num_devices的数量,当我尝试输入CUDA_VISIBLE_DEVICES=0,1 python3 -m alpa.test_install,还是会有相同的问题

@caixiiaoyang
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你有几张卡,num_stages默认是2,你的num_devices不能整除num_satges就会出现这个问题,最好保证num_devices为偶数

我的服务器上有5张卡,如下图 image

我应该怎么修改num_devices的数量,当我尝试输入CUDA_VISIBLE_DEVICES=0,1 python3 -m alpa.test_install,还是会有相同的问题

我不知道怎么修改卡的数目,你有五张卡,并且卡的型号也不一样,你在a100上编译的,在3090上运行可能会出问题

@Ghiad
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Ghiad commented Oct 18, 2023

你有几张卡,num_stages默认是2,你的num_devices不能整除num_satges就会出现这个问题,最好保证num_devices为偶数

我的服务器上有5张卡,如下图 image
我应该怎么修改num_devices的数量,当我尝试输入CUDA_VISIBLE_DEVICES=0,1 python3 -m alpa.test_install,还是会有相同的问题

我不知道怎么修改卡的数目,你有五张卡,并且卡的型号也不一样,你在a100上编译的,在3090上运行可能会出问题

我已经解决了这个error,通过在启动ray的时候限制gpu数量ray start --head --num-gpus=2,然后当我继续运行CUDA_VISIBLE_DEVICES=0,1 python3 -m alpa.test_install 另一个error报错了,另外通过CUDA_VISIBLE_DEVICES=0,1可以限定运行的设备,让代码在同一种设备上运行
image

image

@Ghiad
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Ghiad commented Oct 18, 2023

一个愚蠢的错误,一张显卡被其他用户占用了,换另外的显卡就能顺利执行,十分感谢

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